Sr. AI Engineer
Senior AI Engineer
We’re building Navi — Narvar’s agentic AI that automates post-purchase resolution for the world’s leading retailers.
Hundreds of millions of consumers interact with Narvar every year. Navi is our agentic AI that resolves delivery issues, returns, and refunds through natural conversation — powered by IRIS and 74 billion consumer touchpoints.
We're looking for senior AI engineers to own this system end-to-end: architecture, model selection, production operations. You'll help decide what gets built and how.
What You’ll Work On
Design and build conversational AI agents for returns, claims, and customer service experiences
Own agent systems from architecture → implementation → evaluation → production operations
Build RAG / context graph retrieval pipelines that ground agent responses in real company and customer data
Design agent orchestration for multi-step workflows that interact with identity, risk, order, and loyalty systems
Create evaluation frameworks to measure task completion, accuracy, safety, and user satisfaction
Implement guardrails and safety mechanisms — content moderation, hallucination detection, graceful fallbacks
Integrate conversational experiences across web, mobile, SMS, and email channels
Make real decisions around prompt design, model selection, latency/cost/quality tradeoffs, and failure modes
Collaborate with product, design, and ML teams to build systems that are technically sound and product-aware
What We’re Looking For
We care more about judgment and ownership than credentials.
You’re likely a strong fit if you:
Have shipped conversational AI or agent-based systems used by real users in production
Have built production systems on top of LLM APIs and agent frameworks — not just prompt playgrounds, but real integrations involving tool orchestration, context management, and reliability at scale
Have a point of view on model selection tradeoffs — when to use frontier APIs vs. open-weight models (Qwen, Llama, Mistral), and understand the cost, latency, privacy, and capability tradeoffs of each
Understand prompt engineering beyond basics: structured outputs, few-shot learning, chain-of-thought, tool calling
Have built context graph pipelines that go beyond naive retrieval — entity resolution, relationship modeling, and dynamic context assembly from structured and unstructured data
Have designed agent architectures that use function calling, tool execution, or multi-step reasoning
Have strong programming skills in Python or TypeScript
Have experience building and integrating APIs and backend services
Are comfortable reasoning about evaluation, safety, and reliability in non-deterministic systems
Take initiative naturally and are comfortable operating with ambiguity
Signals That You’ll Thrive Here
These aren’t hard requirements, but strong indicators:
You’ve worked in startup or high-ownership environments
You’ve built and operated AI systems in production, including monitoring and incident response
You’ve evaluated and iterated on LLM systems for accuracy, hallucination, latency, and cost
You’ve built or integrated MCP servers or similar tool-use infrastructure
You’ve influenced technical direction by earning trust, not by mandate
You use modern tooling (including AI-assisted development workflows) to increase leverage, not outsource thinking
(Note: we care about outcome and judgment, not how flashy your tools are.)
Why AI at Narvar?
Because post-purchase is one of the highest-leverage applications of conversational AI.
We’re building AI agents where:
The problem space is well-defined but complex — returns, claims, and support have clear business logic but messy real-world edge cases
Scale is real — hundreds of millions of consumer interactions per year across major global retailers
Impact is measurable — resolution rates, customer satisfaction, cost savings, not vanity metrics
The work is greenfield — you’re not maintaining a legacy chatbot, you’re building the next generation
You’ll help define where and how AI agents should operate, not just implement someone else’s spec.
Why Narvar ( from an Engineer's perspective?)
Real scale, real customers, real consequences
Startup-level ownership with platform-level impact
Teams that value thinking, judgment, and responsibility
Low ego, high trust, and room to do your best work
We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
#LI-RemoteBelow is the estimated annual salary for this position and does not include the other components that make up a Narvar offer including: annual bonus, equity, and benefits.The range reflects the minimum and maximum target for new hire salaries for the position across the US. Within the range, individual compensation packages are based on factors unique to each candidate, including but not limited to, skill set, education and certifications, and work location. Narvar Pay Range$180,000—$230,000 CADPlease read our Privacy Policy to learn what personal information we collect in connection with your job application, and how we may use and share it.
Apply Now
We’re building Navi — Narvar’s agentic AI that automates post-purchase resolution for the world’s leading retailers.
Hundreds of millions of consumers interact with Narvar every year. Navi is our agentic AI that resolves delivery issues, returns, and refunds through natural conversation — powered by IRIS and 74 billion consumer touchpoints.
We're looking for senior AI engineers to own this system end-to-end: architecture, model selection, production operations. You'll help decide what gets built and how.
What You’ll Work On
Design and build conversational AI agents for returns, claims, and customer service experiences
Own agent systems from architecture → implementation → evaluation → production operations
Build RAG / context graph retrieval pipelines that ground agent responses in real company and customer data
Design agent orchestration for multi-step workflows that interact with identity, risk, order, and loyalty systems
Create evaluation frameworks to measure task completion, accuracy, safety, and user satisfaction
Implement guardrails and safety mechanisms — content moderation, hallucination detection, graceful fallbacks
Integrate conversational experiences across web, mobile, SMS, and email channels
Make real decisions around prompt design, model selection, latency/cost/quality tradeoffs, and failure modes
Collaborate with product, design, and ML teams to build systems that are technically sound and product-aware
What We’re Looking For
We care more about judgment and ownership than credentials.
You’re likely a strong fit if you:
Have shipped conversational AI or agent-based systems used by real users in production
Have built production systems on top of LLM APIs and agent frameworks — not just prompt playgrounds, but real integrations involving tool orchestration, context management, and reliability at scale
Have a point of view on model selection tradeoffs — when to use frontier APIs vs. open-weight models (Qwen, Llama, Mistral), and understand the cost, latency, privacy, and capability tradeoffs of each
Understand prompt engineering beyond basics: structured outputs, few-shot learning, chain-of-thought, tool calling
Have built context graph pipelines that go beyond naive retrieval — entity resolution, relationship modeling, and dynamic context assembly from structured and unstructured data
Have designed agent architectures that use function calling, tool execution, or multi-step reasoning
Have strong programming skills in Python or TypeScript
Have experience building and integrating APIs and backend services
Are comfortable reasoning about evaluation, safety, and reliability in non-deterministic systems
Take initiative naturally and are comfortable operating with ambiguity
Signals That You’ll Thrive Here
These aren’t hard requirements, but strong indicators:
You’ve worked in startup or high-ownership environments
You’ve built and operated AI systems in production, including monitoring and incident response
You’ve evaluated and iterated on LLM systems for accuracy, hallucination, latency, and cost
You’ve built or integrated MCP servers or similar tool-use infrastructure
You’ve influenced technical direction by earning trust, not by mandate
You use modern tooling (including AI-assisted development workflows) to increase leverage, not outsource thinking
(Note: we care about outcome and judgment, not how flashy your tools are.)
Why AI at Narvar?
Because post-purchase is one of the highest-leverage applications of conversational AI.
We’re building AI agents where:
The problem space is well-defined but complex — returns, claims, and support have clear business logic but messy real-world edge cases
Scale is real — hundreds of millions of consumer interactions per year across major global retailers
Impact is measurable — resolution rates, customer satisfaction, cost savings, not vanity metrics
The work is greenfield — you’re not maintaining a legacy chatbot, you’re building the next generation
You’ll help define where and how AI agents should operate, not just implement someone else’s spec.
Why Narvar ( from an Engineer's perspective?)
Real scale, real customers, real consequences
Startup-level ownership with platform-level impact
Teams that value thinking, judgment, and responsibility
Low ego, high trust, and room to do your best work
We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
#LI-RemoteBelow is the estimated annual salary for this position and does not include the other components that make up a Narvar offer including: annual bonus, equity, and benefits.The range reflects the minimum and maximum target for new hire salaries for the position across the US. Within the range, individual compensation packages are based on factors unique to each candidate, including but not limited to, skill set, education and certifications, and work location. Narvar Pay Range$180,000—$230,000 CADPlease read our Privacy Policy to learn what personal information we collect in connection with your job application, and how we may use and share it.
Apply Now